Abstract
This paper proposes and analyzes a bio-inspired field estimation scheme using wireless sensor networks. The proposed scheme exploits the temporal pattern of the sensed process to reduce the number of samples sent back to the sink by a sensor node and, as consequence, decrease the energy consumption in data transmission. The proposed scheme is orthogonal to the techniques that reduce the spatial density of collected samples deactivating nodes with similar measurements. Thus, the proposed scheme can be used along with these techniques. We present two variations of this scheme: a sample-bounded and an error-bounded. The sample-bounded limits the maximum number of samples sent back to the sink, while the error-bounded guarantees the observation of every event of interest. Results show that for very regular processes the scheme can reduce up to 90% the total amount of samples sent in the network and even for less regular processes the proposed scheme can reduce the total amount of samples sent from approximately 10 up to 20%, with small reconstruction errors.
Résumé
Cet article propose et analyse un schéma d’estimation de champ bio-inspiré utilisant des réseaux de capteurs. Cette méthode exploite le motif temporel du processus capté pour réduire le nombre d’échantillons envoyés au récepteur par un noeud capteur et, par voie de conséquence, permet de réduire la consommation énergétique de la transmission. Ce schéma étant orthogonal aux techniques qui réduisent la densité spatiale des échantillons collectés en désactivant les noeuds donnant des mesures semblables, il peut être utilisé conjointement avec elles. Deux variantes sont proposées : la première limite le nombre maximal d’échantillons renvoyés au récepteur, la seconde garantit que tout événement intéressant sera observé. Les résultats indiquent que pour des processus très réguliers, il est possible de réduire de près de 90 % le nombre total d’échantillons envoyés dans le réseau et que lorsque les processus sont moins réguliers, la diminution peut tout de même atteindre 10 à 20% avec des erreurs de reconstruction faibles.
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Cunha, D.d.O., Laufer, R.P., Moraes, I.M. et al. A bio-inspired field estimation scheme for wireless sensor networks. Ann. Télécommun. 60, 806–818 (2005). https://doi.org/10.1007/BF03219948
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DOI: https://doi.org/10.1007/BF03219948